In this document, we will introduce how to convert the ONNX model into a model that can be used on the C3V NPU. The first part introduces the working environment needed for model conversion. The second part introduces the steps of conversion.
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1. Environment
NN toolkit installation completed
NN IDE installation completed
Download acuity_examples_c901149.tgz for model conversation
The NPU kernel driver, NN Toolkit, and NN IDE need to match the version:
NPU Kernel Driver | NN Toolkit | NN IDE |
v6.4.13.8 | 6.18.1 | 5.7.2 |
v6.4.15.9 | 6.21.1 | 5.8.2 |
v6.4.18.5 | 6.30.7 | 5.10.1 |
1.1. Prepare NN Toolkit Environment
Please refer to this document: Vivante ACUITY Toolkit
Export environment variable.
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export ACUITY_PATH=/home/users/data/share/c3v/acuity-toolkit-whl-6.18.1/bin |
1.2. Install the IDE
Please refer to this document: VivanteIDE Install
1.3. Uncompress Examples
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tar xvf acuity_examples_c901149.tgz |
Suppose the fold is named c3v. The file path is as follows
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Create Script Soft Connection.
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cd Model
source env.sh |
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1.4. Demo Video
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2. Transfer
2.1. Preparing
Create Model folder
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mkdir yolov8s
cd yolov8s |
Copy the ONNX file as the input. copy the input.jpg which resolution is 640x640. Please make sure the folder name is as same as the ONNX file name.
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cp ../yolov8s.onnx .
cp ../input.jpg . |
Create a dataset.txt file, the content of dataset.txt is the input.jpg file name.
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./input.jpg |
Create inputs_outputs.txt file and get the information from yolov8s.onnx via netron tool/webpage.
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write --input-size-list and --outputs informations to inputs_outputs.txt:
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--inputs images --outputs 'onnx::Reshape_329 onnx::Reshape_344 onnx::Reshape_359' --input-size-list '3,640,640' |
After completing the above steps, there will be the following files under yolov8s：
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2.2. Implementing
Import
This command will import and translate an NN model to ACUITY formats. Execute the command in the console or terminal, and wait for it to complete.
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./pegasus_import.sh yolov8s |
After the command execution is completed, you will see the following four files added under the folder.
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Quantize
Please modify the scale value(1/255) of yolov8s_inputmeta.yml.
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Please select one quantized type for your need, such as uint8 / int16 / bf16 / pcq .
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./pegasus_quantize.sh yolov8s uint8 |
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After the command execution is completed, you will see the following two files added under the folder.
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Inference
Inference the NN model with the quantization data type.
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./pegasus_inference.sh yolov8s uint8 |
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Export
Export the quantized application for device deployment. If you want to get the network binary, please modify the pegasus_export_ovx.sh for the nb file generating, and add both 3 lines marked in the red box.
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./pegasus_export_ovx.sh yolov8s uint8 |
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We can get the NB file and a c file for NN graph setup information.
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2.3. Demo Video
This video is the demo for yolov8s-detection int16 quantize.
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